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Build retrieval + generation systems that stay fast under load
Quick Answer: For most users, the RTX 4070 Ti Super 16GB ($750-$850) offers the best balance of VRAM, speed, and value. Budget builders should consider the RTX 3060 12GB ($250-$350), while professionals should look at the RTX 4090 24GB.
RAG workloads are mixed by nature: embeddings and rerankers need fast, efficient inference, while generation needs VRAM headroom. The right GPU depends on whether you prioritize ingestion speed, interactive chat latency, or multi-user API throughput.
Compare all recommendations at a glance.
| GPU | VRAM | Price | Best For | |
|---|---|---|---|---|
RTX 3060 12GBBudget Pick | 12GB | $250-$350 | Personal knowledge bases, Small team docs search | |
RTX 4070 Ti Super 16GBEditor's Choice | 16GB | $750-$850 | Internal support copilots, Mixed embedding + generation pipelines | |
RTX 4090 24GBPerformance King | 24GB | $1,600-$2,000 | High-quality answer generation, Long-context enterprise docs |
Detailed breakdown of each GPU option with pros and limitations.
Best low-cost entry for small-to-mid RAG stacks. Handles embedding + 7B generation with disciplined context settings.
Best For
Limitations
Strong balance for production-like RAG. Enough VRAM to run better generation models while keeping retrieval responsive.
Best For
Best single-GPU choice for serious local RAG. More room for larger generators, bigger contexts, and multi-user traffic.
Best For